The multilayer connectome of Caenorhabditis elegans
arXiv:1608.08793 · doi:10.1371/journal.pcbi.1005283
Abstract
Connectomics has focused primarily on the mapping of synaptic links in the brain; yet it is well established that extrasynaptic volume transmission, especially via monoamines and neuropeptides, is also critical to brain function. Here we present a draft monoamine connectome, along with a partial neuropeptide connectome, for the nematode C. elegans, based on new and published expression data for biosynthetic genes and receptors. Thus, the neuronal connectome can be represented as a multiplex network, with synaptic, gap junction, and neuromodulatory layers representing alternative modes of interneuronal interaction and with distinct network structures. In particular, the monoamine network exhibits novel topological properties, with a highly disassortative star-like structure and a rich-club of interconnected broadcasting hubs. Despite the low degree of overlap between layers, we find highly significant modes of interaction, pinpointing network locations and multilink motifs where aminergic and neuropeptide signalling modulate synaptic activity. The multilayer connectome of C. elegans represents a clear exemplar of a biological multiplex network and provides a prototype for understanding how extrasynaptic signalling can be integrated into the wired circuitry in larger brains.
References in corpus (17)
- Emergence of scaling in random networks
- The structure and function of complex networks
- Modularity and community structure in networks
- Assortative mixing in networks
- Evolutionary dynamics of group interactions on structured populations: A review
- Community structure in directed networks
- Detecting rich-club ordering in complex networks
- Structural Properties of the Caenorhabditis elegans Neuronal Network
- Layer aggregation and reducibility of multilayer interconnected networks
- The Rich-Club Phenomenon In The Internet Topology
- MuxViz: A Tool for Multilayer Analysis and Visualization of Networks
- Statistical Mechanics of Multiplex Ensembles: Entropy and Overlap
- Measuring and modelling correlations in multiplex networks
- Weighted Multiplex Networks
- Learning and innovative elements of strategy adoption rules expand cooperative network topologies
- Topological Generalizations of network motifs
- Synchronization in weighed scale-free networks with degree-degree correlation
Cited by in corpus (27)
- The physics of brain network structure, function, and control
- Control of Dynamics in Brain Networks
- Multilayer Brain Networks
- Neural signal propagation atlas of C. elegans
- Complex Networks from Classical to Quantum
- Centralities of Nodes and Influences of Layers in Large Multiplex Networks
- Delay controls chimera relay synchronization in multiplex networks
- Birth and stabilization of phase clusters by multiplexing of adaptive networks
- Multilink Communities of Multiplex Networks
- Stability of spontaneous, correlated activity in mouse auditory cortex
- Effect of Topology upon Relay Synchronization in Triplex Neuronal Networks
- Multilayer Network Science: from Cells to Societies
- Disrupted core-periphery structure of multimodal brain networks in Alzheimer's Disease
- Nine Quick Tips for Analyzing Network Data
- Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network
- Multilayer Network Modeling of Integrated Biological Systems
- Topology and dynamics of higher-order multiplex networks
- Developmental trajectory of Caenorhabditis elegans nervous system governs its structural organization
- Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons
- Hyper-diffusion on multiplex networks
- Multilayer adaptive networks in neuronal processing
- Multiscale modeling of brain network organization
- Mask Combination of Multi-layer Graphs for Global Structure Inference
- The State of the Art in Multilayer Network Visualization
- Brain functions emerge as thermal equilibrium states of the connectome
- Strong connectivity and its applications
- Learning dynamic representations of the functional connectome in neurobiological networks